Incremental Clustering for Hierarchical Clustering

被引：2
|
作者：
Narita, Kakeru [1 ]
Hochin, Teruhisa [2 ]
Nomiya, Hiroki [2 ]
机构：
[1] Kyoto Inst Technol, Grad Sch Informat Sci, Kyoto, Japan
[2] Kyoto Inst Technol, Informat & Human Sci, Kyoto, Japan
来源：
2018 5TH INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE/ INTELLIGENCE AND APPLIED INFORMATICS (CSII 2018) | 2018年
关键词：
hierarchical clustering; incremental clustering; data insertion; THINGS IOT; INTERNET;
D O I：
10.1109/CSII.2018.00025
中图分类号：
TP39 [计算机的应用];
学科分类号：
081203 ; 0835 ;
摘要：
This paper proposes a clustering algorithm for updating clusters without reclustering when a point is inserted. We define the center and the radius of the cluster, and update clustering results of points using them. We introduce the concept of outliers and also consider the change in the number of clusters caused by data insertion. From comparative experiments with reclustering by the conventional method, it is shown that the proposed method can cluster points with short calculation time.
引用
收藏
页码：102 / 107
页数：6
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